By Ramkrishna Mukherjee
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Extra resources for Classification in Social Research
Sample text
Clusters of specimens may be located at certain income-points. In that case, an analysis of these clusters is useful to appreciate the nature of the income distribution. By themselves, however, the clusters will not present a systematic and comprehensive grouping of the specimens into mutually distinct and analogous classes. The cut-off points to identify clusters in the income distribution are a matter of subjective judgment by the researchers. Should the extreme points in income distribution, accepted by one researcher as forming a cluster, be left out by another because, in the latter's opinion, these points are poorly represented by numbers of specimen?
The context of classification is as important as the measure of classification, and both must be considered in as many ways as possible and necessary. We shall illustrate this point with reference to a trait which is formulated as measurable by an interval scale and of which the scope of measurement is virtually limitless because of decimalization of the numerals employed as the measuring quantities. ) represents a continuous variable distributed on an interval scale of equal distances between the points of measurement.
We may better appreciate the problem by looking further into the examples cited earlier. For example, the ordering of enterprises with respect to the production of material goods usually follows from a consideration of the organization of productive forces in society. It is expressed by a series such as cited earlier or as can be extensively constructed from the Industrial Classification prepared by the Statistical Office of the United Nations (1968). But whether or not such a series, expressed in codes of several digits, can be translated into an interval scale of measurement is a moot point.
